Gene expression analysis identifies a signature related to lymph node metastasis of T1/2 tumors compared to controls
Ketan Patel, Lei Zhang and Deepak Kademani.
Division of Oral and Maxillofacial Surgery, University of Minnesota, Minneapolis, MN 55455
Introduction and Objectives: Lymph node metastasis in early cancers decreases the overall 5-year survival of head and neck squamous cell carcinoma patients by 50%. In addition, there no biomarkers currently that predict if patients with early stage cancers will develop neck disease. Depth of invasion has been a reliable predictor of lymph node metastasis and is used currently to make clinical decisions regarding the utility of a neck dissection as part of an overall surgical treatment plan. In our study, we compared patients with T1/2 squamous cell carcinoma with lymph node metastasis compared to patients with T1/2 tumors without lymph node metastasis using microarrays to find a subset of genes/patients who were more susceptible to metastasis. This will in turn identify patients who may benefit from earlier intervention or interrogation of the neck, aggressive therapy, or alternatively adjuvant therapy.
Methods: Tumors (mRNA) from patient with early T1/2 squamous cell carcinomas with no nodal metastasis (n=12) were compared to patients with T1/2 with nodal metastasis (n=9) using gene expression microarray analysis. A log2 transformation was used to normalize the data and a two-sample t-test was used to compare the two subsets with statistical significance set at p<0.001 due to the high rate of false discovery rates with microarrays. The fold changes were calculated at the original data scale by dividing the average intensity of control by the average intensity in the study sample.
Results: Several significant genes were differentially expressed between the tumor samples with the nodal versus the tumor samples without nodal metastasis (20 genes). These genes showed differential regulation in several different pathways involved in cell division, (SNK genes, ERG 3), cell metabolism (PPAR, phosphorylases) , cell growth (CAK activating factors), Extracellular matrix genes /signal transduction (sparc/Osteonectin) and oncogenic transformation (protein tyrosine phosphatase of receptor G).
Conclusions: Although a previous study demonstrated no evidence of a metastatic signature, our preliminary data suggests that there is a gene signature associated with metastasis. The genes identified were crucial role in ECM signaling, growth induction, increased mitotic activity and oncogenic transformations. We are in the process of validating these genes currently to confirm our dataset using immunohistochemistry and RT-PCR.